Using the eBay auction data

eBay
Auctions—Boosting and Bagging Using the eBay auction data (file
eBayAuctions.csv) with variable Competitive as the outcome variable,
partition the data into training (60%) and validation (40%).

a.
Run a classification tree, using the default controls of ().
Looking at the validation set, what is the overall accuracy? What is
the lift on the first decile?

b.
Run a boosted tree with the same predictors (use function boosting()
in the  package). For the validation set, what is the
overall accuracy? What is the lift on the first decile?

c.
Run a bagged tree with the same predictors (use function bagging() in
the  package). For the validation set, what is the overall
accuracy? What is the lift on the first decile?

d.
Run a random forest (use function random Forest() in package random
Forest with argument  = 4). Compare the bagged tree to the
random forest in terms of validation accuracy and lift on first
decile. How are the two methods conceptually different?

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